Kenta Kawamoto

RA-L, 2025 | Hojoon Lee, Takuma Seno, Jun Jet Tai, Kaushik Subramanian, Kenta Kawamoto, Peter Stone, Peter R. Wurman

Deep reinforcement learning has achieved superhuman racing performance in high-fidelity simulators like Gran Turismo 7 (GT7). It typically utilizes global features that require instrumentation external to a car, such as precise localization of agents and opponents, limiting ...

ICLR, 2025 | Pengcheng Wang, Chenran Li, Catherine Weaver*, Kenta Kawamoto, Masayoshi Tomizuka*, Chen Tang*, Wei Zhan*

Policies learned through Reinforcement Learning (RL) and ImitationLearning (IL) have demonstrated significant potential in achieving advanced performance in continuous control tasks. However, in real-world environments, itis often necessary to further customize a trained pol...

RLC, 2024 | Miguel Vasco*, Takuma Seno, Kenta Kawamoto, Kaushik Subramanian, Pete Wurman, Peter Stone

Racing autonomous cars faster than the best human drivers has been a longstanding grand challenge for the fields of Artificial Intelligence and robotics. Recently, an end-to-end deep reinforcement learning agent met this challenge in a high-fidelity racing simulator, Gran Tu...

RAL, 2024 | Catherine Weaver*, Chen Tang*, Ce Hao*, Kenta Kawamoto, Masayoshi Tomizuka*, Wei Zhan*

Autonomous racing poses a significant challenge for control, requiring planning minimum-time trajectories under uncertain dynamics and controlling vehicles at their handling limits. Current methods requiring hand-designed physical models or reward functions specific to each ...

RAL, 2024 | Ce Hao*, Catherine Weaver*, Chen Tang*, Kenta Kawamoto, Masayoshi Tomizuka*, Wei Zhan*

Hierarchical reinforcement learning (RL) can accelerate long-horizon decision-making by temporally abstracting a policy into multiple levels. Promising results in sparse reward environments have been seen with skills , i.e. sequences of primitive actions. Typically, a skill ...

NATURE, 2022 | Pete Wurman, Samuel Barrett, Kenta Kawamoto, James MacGlashan, Kaushik Subramanian, Thomas Walsh, Roberto Capobianco, Alisa Devlic, Franziska Eckert, Florian Fuchs, Leilani Gilpin, Piyush Khandelwal, Varun Kompella, Hao Chih Lin, Patrick MacAlpine, Declan Oller, Takuma Seno, Craig Sherstan, Michael D. Thomure, Houmehr Aghabozorgi, Leon Barrett, Rory Douglas, Dion Whitehead Amago, Peter Dürr, Peter Stone, Michael Spranger, Hiroaki Kitano

Many potential applications of artificial intelligence involve making real-time decisions in physical systems while interacting with humans. Automobile racing represents an extreme example of these conditions; drivers must execute complex tactical manoeuvres to pass or block...

NEURIPS, 2021 | Ryuji Imamura, Takuma Seno, Kenta Kawamoto, Michael Spranger

When humans play virtual racing games, they use visual environmental information on the game screen to understand the rules within the environments. In contrast, a state-of-the-art realistic racing game AI agent that outperforms human players does not use image-based environ...